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Cloud-Based Benchmarking of Medical Image Analysis

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Cover of 'Cloud-Based Benchmarking of Medical Image Analysis'

Table of Contents

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    Book Overview
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    Chapter 1 VISCERAL: Evaluation-as-a-Service for Medical Imaging
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    Chapter 2 Using the Cloud as a Platform for Evaluation and Data Preparation
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    Chapter 3 Ethical and Privacy Aspects of Using Medical Image Data
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    Chapter 4 Annotating Medical Image Data
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    Chapter 5 Datasets Created in VISCERAL
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    Chapter 6 Evaluation Metrics for Medical Organ Segmentation and Lesion Detection
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    Chapter 7 VISCERAL Anatomy Benchmarks for Organ Segmentation and Landmark Localization: Tasks and Results
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    Chapter 8 Retrieval of Medical Cases for Diagnostic Decisions: VISCERAL Retrieval Benchmark
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    Chapter 9 Automatic Atlas-Free Multiorgan Segmentation of Contrast-Enhanced CT Scans
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    Chapter 10 Multiorgan Segmentation Using Coherent Propagating Level Set Method Guided by Hierarchical Shape Priors and Local Phase Information
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    Chapter 11 Automatic Multiorgan Segmentation Using Hierarchically Registered Probabilistic Atlases
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    Chapter 12 Multiatlas Segmentation Using Robust Feature-Based Registration
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    Chapter 13 Combining Radiology Images and Clinical Metadata for Multimodal Medical Case-Based Retrieval
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    Chapter 14 Text- and Content-Based Medical Image Retrieval in the VISCERAL Retrieval Benchmark
Attention for Chapter 10: Multiorgan Segmentation Using Coherent Propagating Level Set Method Guided by Hierarchical Shape Priors and Local Phase Information
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Chapter title
Multiorgan Segmentation Using Coherent Propagating Level Set Method Guided by Hierarchical Shape Priors and Local Phase Information
Chapter number 10
Book title
Cloud-Based Benchmarking of Medical Image Analysis
Published by
Springer International Publishing, May 2017
DOI 10.1007/978-3-319-49644-3_10
Book ISBNs
978-3-31-949642-9, 978-3-31-949644-3
Authors

Chunliang Wang, Örjan Smedby

Editors

Allan Hanbury, Henning Müller, Georg Langs

View on publisher site
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 1 Mendeley reader of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 1 100%

Demographic breakdown

Readers by professional status Count As %
Lecturer > Senior Lecturer 1 100%
Readers by discipline Count As %
Materials Science 1 100%

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